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Overview
Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. Special cases of the regression model, ANOVA and ANCOVA will be covered as well. Analysis of residuals and variability will be investigated. The Regression Models course offered by Coursera in partnership Johns Hopkins University will cover modern thinking on model selection and novel uses of regression models including scatterplot smoothing.
What you will learn
- Use regression analysis, least squares and inference
- Understand ANOVA and ANCOVA model cases
- Investigate analysis of residuals and variability
- Describe novel uses of regression models such as scatterplot smoothing
Get more details
Visit programme websiteProgramme Structure
Courses include:
- Least Squares and Linear Regression
- Linear Regression & Multivariable Regression
- Multivariable Regression, Residuals, & Diagnostics
- Logistic Regression and Poisson Regression
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 1 months
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
- Self-paced
Disciplines
Applied Mathematics Machine Learning View 265 other Short Courses in Machine Learning in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Make sure you meet all requirements
Visit programme websiteTuition Fee
To always see correct tuition fees
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
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